Spatial decision-making method and device for site selection and layout of indemnificatory housing

Abstract

The invention discloses a spatial decision-making method and a spatial decision-making device for site selection and layout of indemnificatory houses. Performing gridding sampling on the reference land price data of the residential land to obtain reference land price sampling points; performing spatial interpolation on the land price sampling points to obtain reference land price information; screening out a plot of which the reference land price is lower than a set value from the land price information as a first area; selecting a space with a distance smaller than or equal to a preset distance from the center of the city as a second area; taking an intersection of the first area, the second area and the planned land to obtain a candidate area of the indemnificatory housing; and obtaining a public service facility reachability score of the land parcel in the candidate area, arranging the indemnificatory housing according to the reachability score, and calculating a local spatial isolation index of each street to obtain an indemnificatory housing layout scheme. According to the invention, geographic information and application family data can be analyzed and processed, and the accuracy of site selection and layout is improved. By simulating different housing layout schemes and calculating spatial isolation indexes, excessive gathering of low and medium income families is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of site selection and layout of affordable housing, and in particular to a spatial decision-making method and device for site selection and layout of affordable housing. Background Art

[0002] With the rapid development of urbanization, the fair and effective allocation and configuration of affordable housing has become an urgent challenge for many cities. Existing methods and technologies for the site selection and layout of affordable housing often face the following problems: in terms of construction site selection, due to land costs and complex real estate market conditions, traditional affordable housing projects are often built in urban fringe areas, ignoring the needs of low- and middle-income residents for basic public services such as education, medical care and transportation; in terms of construction layout, existing technologies do not fully consider the large-scale concentrated construction of affordable housing that may lead to residential space isolation and social class differentiation, which is likely to increase social problems. In response to the above problems, a systematic solution that takes into account the site selection and layout process of affordable housing is urgently needed. Summary of the invention

[0003] The present invention solves the above-mentioned technical problems existing in the prior art by providing a spatial decision-making method and device for site selection and layout of affordable housing.

[0004] The present invention provides a spatial decision-making method for site selection and layout of affordable housing, comprising:

[0005] Conduct grid sampling on the obtained residential land benchmark price data to obtain residential land benchmark price sampling points;

[0006] Perform spatial interpolation on the residential land benchmark price sampling points, remove the area corresponding to the non-construction land, and obtain the residential land benchmark price information that can reflect the land supply cost;

[0007] Filter out the plots of land with a benchmark land price lower than a set upper limit value from the benchmark land price information of residential land as the first candidate area;

[0008] Select a spatial range whose distance from the town center is less than or equal to a preset distance as the second candidate area;

[0009] Taking the intersection of the first candidate area, the second candidate area and the planned residential land parcel to obtain a candidate area for affordable housing construction;

[0010] Obtain the accessibility scores of public service facilities of each block in the candidate area for affordable housing construction, arrange affordable housing in descending order according to the accessibility scores of public service facilities of each block, and use the formula Calculate the local spatial isolation index of each street; where i and j are street areas; n is the total number of streets in the city; bi is the number of affordable housing households living in street i; a j is the number of households living in commercial housing in street j; c ij is the adjacency weight matrix; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the adjacent streets of i; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the whole city;

[0011] When the local spatial isolation index LSI of a street reaches or exceeds the preset upper limit, the number of affordable housing construction in that area will be stopped, and the layout of affordable housing in other streets will be increased until an affordable housing layout plan is obtained in which the local spatial isolation index LSI of each street is within an acceptable range.

[0012] Specifically, the selecting of a spatial range whose distance from the town center is less than or equal to a preset distance as the second candidate area includes:

[0013] Based on the obtained data of points of interest of various functional facilities, the kernel density analysis, hot spot analysis and weighted overlay analysis methods are used to comprehensively identify the center of the city;

[0014] Using buffer analysis, an area within a preset maximum radiation distance from the center of the city is selected as the second candidate area.

[0015] Specifically, the accessibility scores of public service facilities of each block in the candidate area for affordable housing construction are obtained, including:

[0016] According to the point of interest data of various public service facilities, multiple buffer distances are set to establish non-overlapping multi-ring buffers;

[0017] Assigning a score to each buffer ring in the non-overlapping multi-ring buffer, with the score decreasing from the center to the periphery, to obtain score information of the non-overlapping multi-ring buffer layer;

[0018] The score information of the non-overlapping multi-ring buffer layer is marked in the candidate area for affordable housing construction, and the accessibility score of the public service facilities of each block in the candidate area for affordable housing construction is obtained.

[0019] Specifically, after obtaining the affordable housing layout plan in which the local spatial segregation index LSI of each street is within an acceptable range, it also includes:

[0020] Perform spatial interpolation on the sample prices of commodity housing projects and affordable housing projects, remove the areas corresponding to non-construction land, and obtain commodity housing market price information and affordable housing guidance price information respectively;

[0021] Subtract the affordable housing guidance price information from the commodity housing market price information to obtain a spatial welfare score;

[0022] For the affordable housing with higher spatial welfare scores in the affordable housing layout plan, the purchase price, rental price and / or the period of use are increased to obtain an optimized affordable housing layout plan; for the affordable housing with lower spatial welfare scores in the affordable housing layout plan, the purchase price, rental price and / or the period of use are reduced to obtain an optimized affordable housing layout plan.

[0023] Specifically, it also includes:

[0024] Application information for applicants who received affordable housing;

[0025] Calculating the demand score of affordable housing for each applicant by weighted summing up the data in the application information;

[0026] Based on the housing preference information in the application information, affordable housing in the affordable housing layout plan is allocated to each applicant in order from large to small according to the demand score.

[0027] The present invention also provides a spatial decision-making device for site selection and layout of affordable housing, comprising:

[0028] A grid sampling unit is used to perform grid sampling on the obtained residential land benchmark price data to obtain residential land benchmark price sampling points;

[0029] A first spatial interpolation unit is used to perform spatial interpolation on the residential land benchmark price sampling points, remove the area corresponding to the non-construction land, and obtain the residential land benchmark price information that can reflect the land supply cost;

[0030] A first candidate area screening unit, configured to screen out plots of land with a base price lower than a set upper limit value from the base price information of residential land as first candidate areas;

[0031] A second candidate area selection unit, used to select a spatial range with a distance from the town center that is less than or equal to a preset distance as the second candidate area;

[0032] The affordable housing construction candidate area obtaining unit is used to obtain the affordable housing construction candidate area by taking the intersection of the first candidate area, the second candidate area and the planned residential land parcel;

[0033] A public service facility accessibility score obtaining unit, used to obtain the public service facility accessibility score of each block in the candidate area for affordable housing construction;

[0034] The local spatial isolation index calculation unit is used to arrange affordable housing in descending order according to the accessibility scores of public service facilities in each block, and calculate the accessibility scores through the formula Calculate the local spatial isolation index of each street; where i and j are street areas; n is the total number of streets in the city; b i is the number of affordable housing households living in street i; a j is the number of households living in commercial housing in street j; c ij is the adjacency weight matrix; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the adjacent streets of i; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the whole city;

[0035] The affordable housing layout plan obtaining unit is used to stop the layout of affordable housing construction in a certain street when the local spatial isolation index LSI of the street reaches or exceeds the preset upper limit value, and increase the layout of affordable housing in other streets at the same time, until an affordable housing layout plan is obtained in which the local spatial isolation index LSI of each street is within an acceptable range.

[0036] Specifically, the second candidate region selection unit includes:

[0037] The city center identification subunit is used to comprehensively identify the city center using kernel density analysis, hot spot analysis and weighted overlay analysis methods based on the obtained data of points of interest of various functional facilities;

[0038] The second candidate area selection subunit is used to use buffer zone analysis to select an area within a preset maximum radiation distance from the center of the city as the second candidate area.

[0039] Specifically, the public service facility accessibility score obtaining unit includes:

[0040] The multi-ring buffer establishment subunit is used to set multiple buffer distances for the obtained point of interest data of various public service facilities and establish non-overlapping multi-ring buffers;

[0041] The buffer ring assignment subunit is used to assign a score to each buffer ring in the non-overlapping multi-ring buffer, with the score decreasing from the center to the periphery, to obtain the score information of the non-overlapping multi-ring buffer layer;

[0042] The score information identification subunit is used to identify the score information of the non-overlapping multi-ring buffer layer to the candidate area for affordable housing construction, and obtain the public service facility accessibility score of each block in the candidate area for affordable housing construction.

[0043] Specifically, it also includes:

[0044] The second spatial interpolation unit is used to perform spatial interpolation on the obtained sample point prices of commodity housing projects and the sample point prices of affordable housing projects, remove the areas corresponding to non-construction land, and obtain commodity housing market price information and affordable housing guidance price information respectively;

[0045] A space welfare score obtaining unit, configured to obtain a space welfare score by subtracting the guide price information of the affordable housing from the market price information of the commodity housing;

[0046] The affordable housing layout plan optimization unit is used to increase the purchase price, rental price and / or shorten the use period of affordable housing with a higher space welfare score in the affordable housing layout plan to obtain an optimized affordable housing layout plan; for affordable housing with a lower space welfare score in the affordable housing layout plan, reduce the purchase price, rental price and / or extend the use period to obtain an optimized affordable housing layout plan.

[0047] Specifically, it also includes:

[0048] An application information obtaining unit, used to obtain application information of applicants for affordable housing;

[0049] A demand score calculation unit, used to calculate the demand score of affordable housing for each applicant by weighted summing up various data in the application information;

[0050] The affordable housing allocation unit is used to allocate affordable housing in the affordable housing layout plan to each applicant in order from large to small according to the demand score based on the housing preference information in the application information.

[0051] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0052] 1. First, grid sampling is performed on the obtained residential land benchmark price data to obtain residential land benchmark price sampling points; then, spatial interpolation is performed on the residential land benchmark price sampling points to eliminate the areas corresponding to non-construction land to obtain residential land benchmark price information that can reflect the land supply cost; then, from the residential land benchmark price information, plots with benchmark prices lower than the set upper limit are selected as the first candidate areas; a spatial range with a distance less than or equal to a preset distance from the town center is selected as the second candidate area; the first candidate area, the second candidate area, and the planned residential land plots are selected. Take the intersection to obtain the candidate area for affordable housing construction; then obtain the accessibility score of public service facilities of each block in the candidate area for affordable housing construction, arrange the affordable housing in descending order according to the accessibility score of public service facilities of each block, and calculate the local spatial isolation index of each street; when the local spatial isolation index of a street reaches or exceeds the preset upper limit, stop arranging the number of affordable housing construction in the area, and increase the layout of affordable housing in other streets at the same time, until the local spatial isolation index of each street is within an acceptable range. The layout plan of affordable housing is obtained. The present invention can analyze and process geographic information and application family data more accurately, can be more dynamic and responsive to market and social changes, not only improves the accuracy of site selection and layout, but also makes the allocation of affordable housing more reasonable, thereby optimizing resource utilization efficiency and response speed. By simulating different housing layout plans and calculating the spatial isolation index, the excessive agglomeration of low- and middle-income families is effectively avoided, which helps to achieve community diversification and promote social integration and harmony.

[0053] 2. By analyzing the specific needs and living preferences of applicant families, we can achieve personalized allocation of housing resources, which not only improves the fairness of housing allocation, but also enhances residents' satisfaction and quality of life. At the same time, by accurately calculating spatial welfare and adjusting housing purchase (rental) prices and usage periods, we promote the equal distribution of spatial welfare, fully consider the differences in spatial welfare and residents' needs in different spatial locations, and make the allocation of public service resources more reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a flow chart of a spatial decision-making method for site selection and layout of affordable housing provided by an embodiment of the present invention;

[0055] Figure 2 is a schematic diagram of a digital elevation model (DEM) of a benchmark land price for residential land in an embodiment of the present invention;

[0056] Figure 3 is a schematic diagram of evaluating the accessibility of public service facilities in a candidate area for affordable housing construction in an embodiment of the present invention;

[0057] Figure 4is a schematic diagram of computing space welfare in an embodiment of the present invention;

[0058] Figure 5 It is a module diagram of a spatial decision-making device for site selection and layout of affordable housing provided by an embodiment of the present invention;

[0059] Figure 6 The module and flow chart of the spatial decision support system for site selection, layout and allocation of affordable housing are constructed by the spatial decision method and device for site selection and layout of affordable housing provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0060] The embodiments of the present invention solve the technical problems existing in the prior art by providing a spatial decision-making method and device for site selection and layout of affordable housing.

[0061] The technical solution in the embodiment of the present invention is to solve the technical problems existing in the prior art, and the overall idea is as follows:

[0062] A. Basic information input

[0063] Input the information of families applying for affordable housing and basic urban geographic information, screen out applicant families that are eligible to purchase (rent) housing, and establish a database of affordable housing to be built and a database of basic urban geographic information.

[0064] A1. Input applicant family information: The initial input covers the basic information of all families applying for affordable housing in the city, including the family’s economic status, current housing status, family member information, and specific housing preference information.

[0065] A2. Review of eligibility for purchasing (renting) housing and establishment of a database to be built: Based on the local affordable housing policy, the eligibility of applicant families for purchasing (renting) housing is reviewed, and the data that pass the review is assigned an ID and stored in the database to be built.

[0066] A3. Input basic geographic information of the city: input the city's land use planning data, benchmark land price map for residential land, sample price data for commodity housing projects, sample price data for affordable housing projects, and point of interest (POI) data for commercial, medical, educational, cultural, public transportation, financial services and other facilities.

[0067] B. Housing Demand and Residential Preference Processing

[0068] The housing needs are ranked according to the family's economic status, housing conditions and other factors, and a database of the applicant family's housing preference information is established on this basis. The specific steps are as follows:

[0069] B1. Calculate and sort housing demand to form a priority ranking database to be built;

[0070] B2. Processing residential preference information: Extract residential preference information from the database to be built in the priority ranking in step B1, sort out its space preferences and room type preferences respectively, and store them in the corresponding database. At the same time, identify and adjust preference information that does not meet the regulations, such as excessive room area or unreasonable location selection. Among them, spatial preference information includes geographical location, and room type preference information includes spatial living area, room layout, floor, orientation and lighting, etc. Based on the family space preference information, the family's needs for work-life balance can be accurately met, reducing traffic congestion and time costs. Based on the room type preference information, the needs of families in different family life cycles can be accurately met.

[0071] C. Preliminary site selection considering land cost and geographical location

[0072] Through geographic information system technology (GIS tools), land costs and geographical locations are comprehensively considered to determine reasonable candidate addresses for affordable housing. For economic reasons, the city center or other high-value areas are not suitable for the construction of affordable housing projects, while too remote locations will affect the living convenience, job opportunities and access to urban infrastructure for low- and middle-income families. Therefore, the location selection will avoid the city center area where land costs are too high, and ensure that it is not too remote to ensure the convenience of residents' lives. To this end, the preliminary site selection steps are as follows:

[0073] C1. Land cost assessment and preliminary screening: Comprehensively consider the actual demolition cost (the demolition cost of the original building) and potential opportunity cost (the loss of income from development for other uses) of the land for affordable housing construction to ensure the economic rationality of the site selection. Among them, the potential opportunity cost is reflected by the local benchmark land price for residential land. The specific steps of land cost assessment and preliminary screening are as follows:

[0074] C11. Construct land supply cost DEM: Perform spatial interpolation on the sampling points of residential land benchmark price and construct a digital elevation model (DEM) of residential land benchmark price. The residential land benchmark price DEM can comprehensively consider land cost and geographical location factors.

[0075] C12. Set an upper limit for land supply costs and preliminarily screen candidate areas: According to the project budget and local policies, set an upper limit for the benchmark land price. This value should reflect the highest land cost that the government can accept to ensure the economic feasibility of the project. Use GIS tools to extract the range value of the benchmark land price DEM for residential land, screen out plots with benchmark land prices below the set upper limit and use them as candidate areas H1.

[0076] C2. Geographic location assessment and preliminary screening: Select a spatial range with a suitable distance from the town center as the candidate area H2 to ensure the convenience of residents' lives.

[0077] C3. Generate candidate sites that comprehensively consider land supply costs and geographical locations: On the basis of excluding high opportunity cost areas in the central area and avoiding overly remote areas, select the best site based on land costs and geographical locations. Using GIS tools, take the intersection of candidate area H1 in step C1 and candidate area H2 in step C2 to obtain candidate area H3 that meets both conditions; take the intersection of candidate area H3 and residential land plots in the land use planning data input in A3 to generate candidate area H4 for affordable housing construction.

[0078] D. Balanced layout considering facility accessibility and residential segregation

[0079] Based on the candidate area H4 for affordable housing construction determined in step C, the actual layout must meet the basic accessibility of public facilities and avoid excessive concentration of low- and middle-income groups to achieve a balanced layout. The specific steps are as follows:

[0080] D1. Evaluate the accessibility of public facilities: Use urban public facility POI data and multi-ring buffer methods to evaluate the accessibility of various public service facilities to candidate areas.

[0081] D2. Layout affordable housing one by one according to the size of accessibility and monitor the local spatial segregation index in real time: Layout affordable housing one by one according to the size of accessibility. Based on the administrative division data at the street scale, the local spatial segregation index of each street is calculated synchronously using the number of families living in commercial housing and the number of families living in affordable housing. In order to avoid excessive agglomeration of low-income families and residential segregation, the number of affordable housing construction within the street range is controlled to prevent the local spatial segregation index from exceeding the upper limit. Specifically, an acceptable upper limit of the local spatial segregation index is set. When the local spatial segregation index of a street reaches or exceeds the upper limit, the number of affordable housing construction in the area is stopped, and the layout of other streets is increased. Specifically, a linear programming model is used to simulate different housing layout plans to ensure that the local spatial segregation index of all streets is within an acceptable range, avoid social segregation, and obtain the best affordable housing layout plan.

[0082] E. Micro-allocation of housing considering spatial welfare and residential preferences

[0083] On the basis of the balanced layout of the number of affordable housing in step D, housing allocation is carried out according to the spatial preference information of the applicant families, and the purchase, rental amount or term of use is adjusted to achieve efficient and fair distribution of housing space benefits. The specific steps are as follows:

[0084] E1. Spatial welfare assessment: The difference between the market price of commercial housing and the guiding price of affordable housing is used to reflect the spatial welfare value contained in affordable housing in a certain area of ​​the city, which is the spatial welfare.

[0085] E2. Adjust the purchase and rental prices and term of use of affordable housing to achieve equal and reasonable distribution of housing space benefits. This method can balance the space benefits obtained by different families when purchasing and renting affordable housing.

[0086] E3. Allocate housing based on space preference and room type preference: Based on the price and period of use adjusted in step E2, allocate housing based on the reasonable family space preference information in the database to be built according to the priority in step B, so that it is as close to the workplace or preferred area as possible to reduce commuting time and transportation costs. After being allocated to the corresponding space area, the specific room type is allocated based on the room type preference, and finally a social housing allocation plan is formed to meet the personalized needs of each applicant family for work and life convenience as much as possible.

[0087] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0088] like Figure 1 As shown, the spatial decision method for site selection and layout of affordable housing provided by the embodiment of the present invention includes:

[0089] Step S110: grid sampling is performed on the obtained residential land benchmark price data to obtain residential land benchmark price sampling points;

[0090] Step S120: performing spatial interpolation on the residential land benchmark price sampling points, eliminating the area corresponding to the non-construction land, and obtaining the residential land benchmark price information that can reflect the land supply cost;

[0091] This step is specifically described. Spatial interpolation is performed on the sampling points of the benchmark land price for residential land, and the areas corresponding to non-construction land are eliminated to obtain the benchmark land price information for residential land that can reflect the land supply cost, including:

[0092] The natural neighbor interpolation method is used to spatially interpolate the sampling points of the benchmark land price for residential land, and the areas corresponding to non-construction land such as rivers and lakes are eliminated to obtain a digital elevation model (DEM) of the benchmark land price for residential land that can reflect the land supply cost, such as Figure 2 shown.

[0093] Step S130: Filter out the plots whose benchmark land prices are lower than the set upper limit value from the benchmark land price information of residential land as the first candidate area;

[0094] Step S140: selecting a spatial range whose distance from the town center is less than or equal to a preset distance as a second candidate area;

[0095] Specifically describing this step, a spatial range whose distance from the town center is less than or equal to a preset distance is selected as the second candidate area, including:

[0096] Based on the obtained data on points of interest of various functional facilities, kernel density analysis, hot spot analysis and weighted overlay analysis methods are used to comprehensively identify the center of the city; it should be noted that the identified city center can be one or more.

[0097] Using buffer analysis, areas within the preset maximum radiation distance from the city center are selected as the second candidate areas to ensure that the location of affordable housing is not too remote and is convenient for residents to commute and daily life.

[0098] Step S150: Taking the intersection of the first candidate area, the second candidate area and the planned residential land parcel to obtain a candidate area for affordable housing construction;

[0099] Step S160: Obtain the accessibility scores of public service facilities of each block in the candidate area for affordable housing construction, and arrange the affordable housing in descending order according to the accessibility scores of public service facilities of each block, that is, give priority to selecting locations with high accessibility of public facilities as the actual construction sites of affordable housing, and arrange the number of affordable housing one by one. And through the formula Calculate the local spatial isolation index of each street; where i and j are street areas; n is the total number of streets in the city; b i is the number of affordable housing households living in street i; a j is the number of households living in commercial housing in street j; c ij is the adjacency weight matrix; its value is 1 when i and j are adjacent, and its value is 0 when i and j are not adjacent. i can be equal to j; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the adjacent streets of i; It indicates the degree of interaction between the affordable housing households in street i and the commercial housing households in the whole city. The local spatial segregation index (LSI) refers to the degree of residential segregation of affordable housing households between spatial units. The larger the value, the greater the degree of segregation.

[0100] Specifically, Figure 3 As shown in the figure, the accessibility scores of public service facilities of each plot in the candidate area for affordable housing construction are obtained, including:

[0101] According to the point of interest data of various public service facilities, multiple buffer distances are set to establish non-overlapping multi-ring buffers;

[0102] Assign a score to each buffer ring in a non-overlapping multi-ring buffer, with the score decreasing from the center to the periphery to reflect the accessibility scores at different distances, and obtain the score information of the non-overlapping multi-ring buffer layer;

[0103] The score information of the non-overlapping multi-ring buffer layers is marked in the candidate areas for affordable housing construction, and the accessibility scores of public service facilities of each block in the candidate areas for affordable housing construction are obtained.

[0104] Step S170: When the local spatial isolation index LSI of a street reaches or exceeds the preset upper limit, stop planning the construction of affordable housing in the area, and increase the layout of affordable housing in other streets until an affordable housing layout plan is obtained in which the local spatial isolation index LSI of each street is within an acceptable range.

[0105] Specifically, the affordable housing layout plan for the entire city is simulated by solving a linear programming model, and finally the affordable housing layout plan with a smaller mean and variance of the local spatial isolation index of each street is selected.

[0106] In order to optimize the affordable housing layout plan, after obtaining the affordable housing layout plan with the local spatial segregation index LSI of each street within an acceptable range, it also includes:

[0107] Perform spatial interpolation on the sample prices of commodity housing projects and affordable housing projects, remove the areas corresponding to non-construction land, and obtain commodity housing market price information and affordable housing guidance price information respectively;

[0108] This step is specifically described. The obtained sample prices of commodity housing projects and affordable housing projects are spatially interpolated, and the areas corresponding to non-construction land are eliminated to obtain commodity housing market price information and affordable housing guidance price information, including:

[0109] Based on GIS tools, the ordinary Kriging spatial interpolation method was used to spatially interpolate the sample prices of commercial housing projects and affordable housing projects, and the areas corresponding to non-construction land such as rivers, lakes, etc. were eliminated to obtain the commercial housing market price DEM and the affordable housing guidance price DEM, respectively.

[0110] Subtract the price information of affordable housing from the market price information of commodity housing to obtain the spatial welfare score;

[0111] This step is described in detail, such as Figure 4 As shown in the figure, the commodity housing market price information is subtracted from the affordable housing guidance price information to obtain the spatial welfare score, including:

[0112] Use raster calculation tools to subtract the affordable housing guidance price DEM from the commodity housing market price DEM to obtain the spatial welfare DEM. The value on the spatial welfare DEM is the spatial welfare score.

[0113] For affordable housing with higher spatial welfare scores in the affordable housing layout plan, the purchase price, rental price and / or the period of use are increased to obtain an optimized affordable housing layout plan; for affordable housing with lower spatial welfare scores in the affordable housing layout plan, the purchase price, rental price and / or the period of use are reduced to obtain an optimized affordable housing layout plan.

[0114] In order to reasonably allocate affordable housing, it also includes:

[0115] Application information for applicants who received affordable housing;

[0116] The demand score of affordable housing for each applicant is calculated by weighted summation of various data in the application information;

[0117] Specifically, based on the economic status, housing status and other factors of the applicant's family, the housing demand of each family is calculated and ranked according to the value to ensure that the families most in need of housing are given priority. Among them, the economic status indicators are the per capita income of the family, the per capita assets of the family, etc., the housing status indicators are the per capita housing area of ​​the family, the safety of the housing building, etc., and the other factor indicators are the needs of special members, employment status, etc.

[0118] The specific steps are as follows: ① Establish scoring criteria and score individual indicators: Establish scoring criteria for each indicator, set the score range to 0-10 points, and then score each indicator of each family to obtain the individual housing demand. For example, the scoring criteria for the household per capita income indicator are: households with a per capita income lower than 10% of the city's median per capita income get 2 points, those with a per capita income lower than 30% get 6 points, and those with a per capita income lower than 50% get 10 points, and so on. ② Set indicator weights: Set weights for different indicators based on local policies and specific needs of the target group. For example, among all indicators, the weight of per capita household income can be set to a relatively large value. ③ Weighted calculation of total housing demand: Weighted individual housing demand of all indicators are added together to obtain the total housing demand of each family. ④ Sort the total housing demand: Sort all applicant families according to the size of the total housing demand to form a priority ranking database to be built. Among them, families with high total housing demand scores will have priority in obtaining affordable housing resources.

[0119] Based on the housing preference information in the application information, the applicants are allocated affordable housing in the affordable housing layout plan in descending order according to the demand score. Among them, the housing preference information includes: geographical location, living space, room layout, floor, orientation and lighting, etc.

[0120] like Figure 5 As shown, the spatial decision-making device for site selection and layout of affordable housing provided by the embodiment of the present invention includes:

[0121] The grid sampling unit 100 is used to perform grid sampling on the obtained residential land benchmark price data to obtain residential land benchmark price sampling points;

[0122] The first spatial interpolation unit 200 is used to perform spatial interpolation on the residential land benchmark price sampling points, remove the area corresponding to the non-construction land, and obtain the residential land benchmark price information that can reflect the land supply cost;

[0123] Specifically, the first spatial interpolation unit 200 is used to perform spatial interpolation on the residential land benchmark price sampling points through the natural neighbor interpolation method, and eliminate the areas corresponding to non-construction land such as rivers, lakes, etc., to obtain a digital elevation model (DEM) of the residential land benchmark price that can reflect the land supply cost.

[0124] The first candidate area screening unit 300 is used to screen out plots of land with a base price lower than a set upper limit value from the base price information of residential land as the first candidate area;

[0125] The second candidate area selection unit 400 is used to select a spatial range whose distance from the town center is less than or equal to a preset distance as the second candidate area;

[0126] Specifically, the second candidate region selecting unit 400 includes:

[0127] The city center identification subunit is used to comprehensively identify the city center based on the point of interest data of various functional facilities obtained by using kernel density analysis, hot spot analysis and weighted overlay analysis methods; it should be noted that the identified city center can be one or more.

[0128] The second candidate area selection subunit is used to use buffer analysis to select areas within a preset maximum radiation distance from the city center as the second candidate area to ensure that the location of the affordable housing is not too remote and is convenient for residents to commute and daily life.

[0129] The affordable housing construction candidate area obtaining unit 500 is used to obtain the affordable housing construction candidate area by taking the intersection of the first candidate area, the second candidate area and the planned residential land parcel;

[0130] The public service facility accessibility score obtaining unit 600 is used to obtain the public service facility accessibility score of each block in the candidate area for affordable housing construction;

[0131] Specifically, the public service facility accessibility score obtaining unit 600 includes:

[0132] The multi-ring buffer establishment subunit is used to set multiple buffer distances for the obtained point of interest data of various public service facilities and establish non-overlapping multi-ring buffers;

[0133] The buffer ring assignment subunit is used to assign a score to each buffer ring in a non-overlapping multi-ring buffer. The score decreases from the center to the periphery to reflect the accessibility scores at different distances, and obtain the score information of the non-overlapping multi-ring buffer layer;

[0134] The score information identification subunit is used to identify the score information of the non-overlapping multi-ring buffer layer to the candidate area for affordable housing construction, and obtain the accessibility score of public service facilities of each block in the candidate area for affordable housing construction.

[0135] The local space isolation index calculation unit 700 is used to arrange the affordable housing in descending order according to the accessibility scores of the public service facilities of each block, that is, to give priority to selecting locations with high accessibility of public facilities as the actual construction sites of affordable housing, and to arrange the number of affordable housing one by one. And through the formula Calculate the local spatial isolation index of each street; where i and j are street areas; n is the total number of streets in the city; b i is the number of affordable housing households living in street i; a j is the number of households living in commercial housing in street j; c ij is the adjacency weight matrix; its value is 1 when i and j are adjacent, and its value is 0 when i and j are not adjacent. i can be equal to j; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the adjacent streets of i; It indicates the degree of interaction between the affordable housing households in street i and the commercial housing households in the whole city. The local spatial segregation index (LSI) refers to the degree of residential segregation of affordable housing households between spatial units. The larger the value, the greater the degree of segregation.

[0136] The affordable housing layout plan obtaining unit 800 is used to stop the layout of affordable housing construction in a certain area when the local space isolation index LSI of a certain street reaches or exceeds a preset upper limit value, and at the same time increase the layout of affordable housing in other streets until an affordable housing layout plan is obtained in which the local space isolation index LSI of each street is within an acceptable range.

[0137] In order to optimize the layout plan of affordable housing, it also includes:

[0138] The second spatial interpolation unit is used to perform spatial interpolation on the obtained sample point prices of commodity housing projects and the sample point prices of affordable housing projects, remove the areas corresponding to non-construction land, and obtain commodity housing market price information and affordable housing guidance price information respectively;

[0139] Specifically, the second spatial interpolation unit is specifically used to perform spatial interpolation on the sample prices of commercial housing projects and the sample prices of affordable housing projects respectively through ordinary Kriging spatial interpolation method based on GIS tools, and eliminate the areas corresponding to non-construction land such as rivers, lakes, etc., to obtain the commercial housing market price DEM and the affordable housing guidance price DEM respectively.

[0140] A space welfare score obtaining unit is used to obtain a space welfare score by subtracting the guidance price information of affordable housing from the market price information of commodity housing;

[0141] Specifically, the spatial welfare score obtaining unit is used to use a raster calculation tool to subtract the affordable housing guidance price DEM from the commodity housing market price DEM to obtain the spatial welfare DEM. The value on the spatial welfare DEM is the spatial welfare score.

[0142] The affordable housing layout plan optimization unit is used to increase the purchase price, rental price and / or shorten the use period of affordable housing with a higher spatial welfare score in the affordable housing layout plan, so as to obtain an optimized affordable housing layout plan; for affordable housing with a lower spatial welfare score in the affordable housing layout plan, reduce the purchase price, rental price and / or extend the use period, so as to obtain an optimized affordable housing layout plan.

[0143] In order to reasonably allocate affordable housing, it also includes:

[0144] An application information obtaining unit, used to obtain application information of applicants for affordable housing;

[0145] A demand score calculation unit, used to calculate the demand score of affordable housing for each applicant by weighted summing up various data in the application information;

[0146] The affordable housing allocation unit is used to allocate affordable housing in the affordable housing layout plan to each applicant in descending order according to the demand score based on the housing preference information in the application information. The housing preference information includes: geographical location, living space, room layout, floor, orientation and lighting, etc.

[0147] Based on the spatial decision method and device for the site selection and layout of affordable housing provided by the embodiment of the present invention, a spatial decision support system for the site selection, layout and allocation of affordable housing is also designed. The system adopts a B / S architecture, the front end is constructed using HTML5, CSS and JavaScript technology, the back end uses Python and Django framework, the database uses PostgreSQL, and the geographic information processing uses ArcGIS Server. Figure 6 As shown, the system includes a data input module, a demand and preference processing module, a preliminary site selection module, a balanced layout module and a housing allocation module. The details are as follows:

[0148] 1. Data input module

[0149] 1.1 Input of family information for affordable housing application

[0150] The system interface provides a family information input module, including basic family information and residential preference information. Basic family information includes family income, family assets, existing housing conditions, basic information of family members, etc. Residential preference information includes preferences for residential areas (specific to districts or streets), living space, room layout, floor, orientation and lighting, etc.

[0151] 1.2 Input of basic urban geographic information

[0152] The system administrator imports basic urban geographic information in batches through the background, including administrative division data, land use planning data, benchmark land price maps for residential land, sample price data for commercial housing projects, sample price data for affordable housing projects, and POI data for commercial, medical, educational, cultural, public transportation, financial services and other facilities.

[0153] 2. Demand and preference processing module

[0154] 2.1 Calculation of housing demand

[0155] Based on the input of family economic status, housing status, etc., the system scores each family according to the preset scoring criteria. For example, a family with an income below 50% of the city median will get 10 points, a family with an income below 30% of the median will get 6 points, and so on.

[0156] The system calculates the total housing demand by weighting each score and ranks the applicant families according to the demand.

[0157] 2.2 Processing of residence preference information

[0158] The space and room type preference information of the family is extracted from the results of the demand ranking and stored in the residential preference information database. The system automatically identifies and adjusts unreasonable preference information. For example, if the area of ​​the selected room exceeds the standard, the system automatically rejects it and notifies the applicant family to modify the preference information.

[0159] 3. Preliminary site selection module

[0160] 3.1 Land cost assessment and preliminary screening

[0161] The system constructs the residential land benchmark price DEM based on the input residential land benchmark price map to evaluate the land cost of each plot. Set the upper limit of the benchmark land price and filter out plots with benchmark land prices below the upper limit as candidate areas.

[0162] 3.2 Geographic location assessment and initial screening

[0163] Kernel density analysis and hot spot analysis are performed on the POI data of public service facilities to identify the single / multiple centers of the city and set the maximum radiation distance parameter Dmax_service of the city center. Based on the maximum radiation distance parameter Dmax_service, GIS tools are used to perform buffer analysis on the plots around the city center to screen out suitable candidate areas.

[0164] 3.3 Generation of candidate regions considering land supply cost and geographical location

[0165] The results of land cost assessment and geographical location assessment are intersected to generate candidate areas that meet the conditions, and then the area is intersected with the residential land in the land use plan to generate the final candidate area for affordable housing.

[0166] 4. Balanced layout module

[0167] 4.1 Assessment of accessibility of public facilities

[0168] Perform a multi-ring buffer analysis on the public service facilities around the candidate area to evaluate the accessibility of facilities in each plot. Assign a score to each buffer ring and calculate the total accessibility score of the plot to generate a candidate area with public facility accessibility information.

[0169] 4.2 Local spatial isolation index calculation and layout optimization

[0170] A linear programming model is used to simulate different housing layout plans and calculate the local spatial segregation index (LSI) of each street in real time. The layout of affordable housing is dynamically adjusted according to the LSI index to avoid excessive agglomeration.

[0171] 5. Housing allocation module

[0172] 5.1 Space welfare assessment

[0173] Construct the commodity housing market price DEM and the affordable housing guidance price DEM and calculate the spatial welfare of different plots to obtain the spatial welfare DEM.

[0174] 5.2 Adjustment of purchase price, lease price and period of use

[0175] According to the level of spatial welfare, the purchase price, rental price and usage period of affordable housing will be adjusted to balance the spatial welfare obtained by different families.

[0176] 5.3 Allocating housing based on residential preferences

[0177] On the basis of adjusting the price and term of use, housing is allocated according to the family's space preference information and room type preference information, to form an affordable housing allocation plan that meets the personalized needs of each family for work and living convenience as much as possible.

[0178] System implementation effect

[0179] By integrating GIS and DSS technologies, this system can accurately analyze and process geographic information and applicant family data, provide dynamic decision support that responds to market and social changes, effectively avoid excessive concentration of low- and middle-income families, and promote social integration and harmony. Through personalized allocation of housing resources, the fairness of housing allocation and residents' satisfaction are improved, and the efficiency of resource utilization is optimized.

[0180] In summary, the embodiments of the present invention propose a spatial decision support method, device and system for the site selection, layout and allocation of affordable housing, which aims to overcome the limitations of traditional affordable housing site selection and layout methods, support more effective and fairer site selection, layout and allocation plans, and achieve reasonable spatial layout of affordable housing resources and reasonable spatial welfare distribution.

[0181] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0182] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0183] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0184] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0185] The parts not described in detail in the embodiments of the present invention are all known technologies to those skilled in the art. Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A spatial decision-making method for the site selection and layout of affordable housing, characterized in that: include: Conduct grid sampling on the obtained residential land benchmark price data to obtain residential land benchmark price sampling points; Perform spatial interpolation on the residential land benchmark price sampling points, remove the area corresponding to the non-construction land, and obtain the residential land benchmark price information that can reflect the land supply cost; Filter out the plots whose benchmark land prices are lower than a set upper limit value from the benchmark land price information of residential land as the first candidate area; Select a spatial range whose distance from the town center is less than or equal to a preset distance as the second candidate area; Taking the intersection of the first candidate area, the second candidate area and the planned residential land parcel to obtain a candidate area for affordable housing construction; Obtain the accessibility scores of public service facilities of each block in the candidate area for affordable housing construction, arrange affordable housing in descending order according to the accessibility scores of public service facilities of each block, and use the formula Calculate the local spatial isolation index of each street; where i and j are street areas; n is the total number of streets in the city; b i is the number of affordable housing households living in street i; a j is the number of households living in commercial housing in street j; c ij is the adjacency weight matrix; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the adjacent streets of i; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the whole city; When the local spatial isolation index LSI of a street reaches or exceeds the preset upper limit, the number of affordable housing construction in that area will be stopped, and the layout of affordable housing in other streets will be increased until an affordable housing layout plan is obtained in which the local spatial isolation index LSI of each street is within an acceptable range.

2. The spatial decision-making method for site selection and layout of affordable housing according to claim 1, characterized in that: The step of selecting a spatial range whose distance from the town center is less than or equal to a preset distance as the second candidate area includes: Based on the obtained data of points of interest of various functional facilities, the kernel density analysis, hot spot analysis and weighted overlay analysis methods are used to comprehensively identify the center of the city; Using buffer analysis, an area within a preset maximum radiation distance from the center of the city is selected as the second candidate area.

3. The spatial decision-making method for site selection and layout of affordable housing according to claim 1, characterized in that: The obtaining of the accessibility scores of public service facilities of each block in the candidate area for affordable housing construction includes: According to the point of interest data of various public service facilities, multiple buffer distances are set to establish non-overlapping multi-ring buffers; Assigning a score to each buffer ring in the non-overlapping multi-ring buffer, with the score decreasing from the center to the periphery, to obtain score information of the non-overlapping multi-ring buffer layer; The score information of the non-overlapping multi-ring buffer layer is marked in the candidate area for affordable housing construction, and the accessibility score of the public service facilities of each block in the candidate area for affordable housing construction is obtained.

4. The spatial decision-making method for site selection and layout of affordable housing according to claim 1, characterized in that: After obtaining the affordable housing layout plan in which the local spatial segregation index LSI of each street is within an acceptable range, the following is further included: Perform spatial interpolation on the sample prices of commodity housing projects and affordable housing projects, remove the areas corresponding to non-construction land, and obtain commodity housing market price information and affordable housing guidance price information respectively; Subtract the affordable housing guidance price information from the commodity housing market price information to obtain a spatial welfare score; For the affordable housing with higher spatial welfare scores in the affordable housing layout plan, the purchase price, rental price and / or the period of use are increased to obtain an optimized affordable housing layout plan; for the affordable housing with lower spatial welfare scores in the affordable housing layout plan, the purchase price, rental price and / or the period of use are reduced to obtain an optimized affordable housing layout plan.

5. The spatial decision-making method for site selection and layout of affordable housing according to any one of claims 1 to 4, characterized in that: Also includes: Application information for applicants who received affordable housing; Calculating the demand score of affordable housing for each applicant by weighted summing up the data in the application information; Based on the housing preference information in the application information, affordable housing in the affordable housing layout plan is allocated to each applicant in order from large to small according to the demand score.

6. A spatial decision-making device for the site selection and layout of affordable housing, characterized in that: include: A grid sampling unit is used to perform grid sampling on the obtained residential land benchmark price data to obtain residential land benchmark price sampling points; A first spatial interpolation unit is used to perform spatial interpolation on the residential land benchmark price sampling points, remove the area corresponding to the non-construction land, and obtain the residential land benchmark price information that can reflect the land supply cost; A first candidate area screening unit, configured to screen out plots of land with a base price lower than a set upper limit value from the base price information of residential land as first candidate areas; A second candidate area selection unit, used to select a spatial range with a distance from the town center that is less than or equal to a preset distance as the second candidate area; The affordable housing construction candidate area obtaining unit is used to obtain the affordable housing construction candidate area by taking the intersection of the first candidate area, the second candidate area and the planned residential land parcel; A public service facility accessibility score obtaining unit, used to obtain the public service facility accessibility score of each block in the candidate area for affordable housing construction; The local spatial isolation index calculation unit is used to arrange affordable housing in descending order according to the accessibility scores of public service facilities in each block, and calculate the accessibility scores through the formula Calculate the local spatial isolation index of each street; where i and j are street areas; n is the total number of streets in the city; b i is the number of affordable housing households living in street i; a j is the number of households living in commercial housing in street j; c ij is the adjacency weight matrix; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the adjacent streets of i; It represents the degree of interaction between the affordable housing households in street i and the commercial housing households in the whole city; The affordable housing layout plan obtaining unit is used to stop the layout of affordable housing construction in a certain street when the local spatial isolation index LSI of the street reaches or exceeds the preset upper limit value, and increase the layout of affordable housing in other streets at the same time, until an affordable housing layout plan is obtained in which the local spatial isolation index LSI of each street is within an acceptable range.

7. The spatial decision-making device for site selection and layout of affordable housing according to claim 6, characterized in that: The second candidate region selection unit includes: The city center identification subunit is used to comprehensively identify the city center using kernel density analysis, hot spot analysis and weighted overlay analysis methods based on the obtained data of points of interest of various functional facilities; The second candidate area selection subunit is used to use buffer zone analysis to select an area within a preset maximum radiation distance from the center of the city as the second candidate area.

8. The spatial decision-making device for site selection and layout of affordable housing according to claim 6, characterized in that: The public service facility accessibility score obtaining unit includes: The multi-ring buffer establishment subunit is used to set multiple buffer distances for the obtained point of interest data of various public service facilities and establish non-overlapping multi-ring buffers; The buffer ring assignment subunit is used to assign a score to each buffer ring in the non-overlapping multi-ring buffer, with the score decreasing from the center to the periphery, to obtain the score information of the non-overlapping multi-ring buffer layer; The score information identification subunit is used to identify the score information of the non-overlapping multi-ring buffer layer to the candidate area for affordable housing construction, and obtain the public service facility accessibility score of each block in the candidate area for affordable housing construction.

9. The spatial decision-making device for site selection and layout of affordable housing according to claim 6, characterized in that: Also includes: The second spatial interpolation unit is used to perform spatial interpolation on the obtained sample point prices of commodity housing projects and the sample point prices of affordable housing projects, remove the areas corresponding to non-construction land, and obtain commodity housing market price information and affordable housing guidance price information respectively; A space welfare score obtaining unit, configured to obtain a space welfare score by subtracting the guide price information of the affordable housing from the market price information of the commodity housing; The affordable housing layout plan optimization unit is used to increase the purchase price, rental price and / or shorten the use period of affordable housing with a higher space welfare score in the affordable housing layout plan to obtain an optimized affordable housing layout plan; for affordable housing with a lower space welfare score in the affordable housing layout plan, reduce the purchase price, rental price and / or extend the use period to obtain an optimized affordable housing layout plan.

10. The spatial decision-making device for site selection and layout of affordable housing according to any one of claims 6 to 9, characterized in that: Also includes: An application information obtaining unit, used to obtain application information of applicants for affordable housing; A demand score calculation unit, used to calculate the demand score of affordable housing for each applicant by weighted summing up various data in the application information; The affordable housing allocation unit is used to allocate affordable housing in the affordable housing layout plan to each applicant in order from large to small according to the demand score based on the housing preference information in the application information.

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